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enum | BetaFunctionSelect { FletcherReves,
PolakRibiere,
ConjugateDescent
} |
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| BackPropagationCGAlgorithm (NeuralNet &theNetwork) |
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double | train (const int numberOfEpochs, const NeuralNetDataSet &dataSet, const NeuralNet::InputNormalisationSelect normaliseTrainingData=NeuralNet::PassthroughNormalised) |
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double | train (const int numberOfEpochs, const NeuralNetDataSet &dataSet, const std::vector< InputNormaliser * > &inputNormalisers) |
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void | setBetaFunction (BetaFunctionSelect theFunction) |
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void | setLinearSearchInitialStepLength (const double stepLength) |
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void | setLinearSearchMu (const double mu) |
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void | setLinearSearchSigma (const double sigma) |
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void | setLinearSearchGamma (const double gamma) |
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void | setLinearSearchMaxIterations (const int maxIterations) |
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void | setLinearSearchAbsGradientCutoff (const double cutoff) |
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void | setEpochsBeforeGradientReset (const int numberOfEpochs) |
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void | setProgressPrintoutFrequency (const int frequency) |
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std::vector< double > | getTrainingErrorValuesPerEpoch () const |
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double | trainWithDataSet (const int numberOfEpochs) |
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std::vector< double > | layerOutput (const int layer) const |
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void | calculateLayerOutputs () |
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void | calculateDerivativeOutputs () |
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void | calculateErrorSignals () |
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void | calculateDeDw () |
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void | calculateRunningDeDw () |
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double | error () |
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double | newEpoch (bool &success, double &gradient) |
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double | processDataSet () |
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double | beta (const std::vector< double > &gk, const std::vector< double > &gkplus1, const std::vector< double > &dk) |
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double | betaFR (const std::vector< double > &gk, const std::vector< double > &gkplus1) |
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double | betaPR (const std::vector< double > &gk, const std::vector< double > &gkplus1) |
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double | betaCD (const std::vector< double > &gk, const std::vector< double > &gkplus1, const std::vector< double > &dk) |
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double | alpha (const std::vector< double > &x, const std::vector< double > &p, const std::vector< double > &g, const double F0, bool &converged) |
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The documentation for this class was generated from the following file: